Biology subjects

Perrin, S.

Publications and source records attributed to Perrin, S..

8 recordsLinked to original sources

bioRxiv2025

The genetic driver of Acute Necrotizing Encephalopathy, RANBP2, regulates the inflammatory response to Influenza A virus infection

Influenza virus infections can cause severe complications such as Acute Necrotizing Encephalopathy (ANE), which is characterised by rapid onset pathological inflammation following febrile infection. Heterozygous dominant mutations in the nucleoporin RANBP2/Nup358 predispose to influenza-triggered ANE1. The aim of our study was to determine whether RANBP2 plays a role in IAV-triggered inflammatory responses. We found that the depletion of RANBP2 in a human airway epithelial cell line increased IAV genomic replication by favouring the import of the viral polymerase subunits, PB1, PB2 and PA following viral transcription and translation. Additionally, RANBP2 knockdown enhanced the cytoplasmic export of viral RNA (vRNA) and disrupted segment stoichiometry, which associated with elevated production of the pro-inflammatory chemokines CXCL8, CXCL10, CCL2, CCL3 and CCL4 in human primary macrophages. Using CRISPR-Cas9 knock-in for the ANE1 disease variant RANBP2-T585M, we further demonstrate that this point mutation causes a loss-of-localisation phenotype that excludes RANBP2 from the nuclear envelope, which phenocopies RANBP2 knockdown by increasing IAV replication and driving pro-inflammatory cytokine expression following infection. Together, our results reveal that RANBP2 regulates influenza RNA replication and nuclear export, thereby restraining virus-induced hyperinflammation, and further suggest that ANE1 pathogenesis results from the impaired localisation of RANBP2 at the nuclear envelope.

immunology↗

bioRxiv2024

Multimodal analyses of immune cells during bone repair identify macrophages as a therapeutic target in musculoskeletal trauma

Musculoskeletal traumatic injuries (MTI) involve soft tissue lesions adjacent to a bone fracture leading to fibrous nonunion. The impact of MTI on the inflammatory response to fracture and on the immunomodulation of skeletal stem/progenitor cells (SSPCs) remains unknown. Here, we used single cell transcriptomic analyses to describe the immune cell dynamics after bone fracture and identified distinct macrophage subsets with successive pro-inflammatory, pro-repair and anti-inflammatory profiles. Concurrently, SSPCs transition via a pro- and anti-inflammatory fibrogenic phase of differentiation prior to osteochondrogenic differentiation. In a preclinical MTI mouse model, the injury response of immune cells and SSPCs is disrupted leading to a prolonged pro-inflammatory phase and delayed resolution of inflammation. Macrophage depletion improves bone regeneration in MTI demonstrating macrophage involvement in fibrous nonunion. Finally, pharmacological inhibition of macrophages using the CSF1R inhibitor Pexidartinib ameliorates healing. These findings reveal the coordinated immune response of macrophages and skeletal stem/progenitor cells as driver of bone healing and as a primary target for the treatment of trauma-associated fibrosis. SummaryHachemi et al. report the immune cell atlas of bone repair revealing macrophages as pro-fibrotic regulators and a therapeutic target for musculoskeletal regeneration. Genetic depletion or pharmacological inhibition of macrophages improves bone healing in musculoskeletal trauma.

physiology↗

bioRxiv2023

PERK modulation, with GSK2606414, Sephin1 or salubrinal, failed to produce therapeutic benefits in the SOD1G93A mouse model of ALS

Amyotrophic lateral sclerosis (ALS) has been linked to overactivity of the protein kinase RNA-like ER kinase (PERK) branch of the unfolded protein response (UPR) pathway, both in ALS patients and mouse models. However, attempts to pharmacologically modulate PERK for therapeutic benefit have yielded inconsistent and often conflicting results. This study sought to address these discrepancies by comprehensively evaluating three commonly used PERK modulators (GSK2606414, salubrinal, and Sephin1) in the same experimental models, with the goal of assessing the viability of targeting the PERK pathway as a therapeutic strategy for ALS. To achieve this goal, a tunicamycin-challenge assay was developed using wild-type mice to monitor changes in liver UPR gene expression in response to PERK pathway modulation. Subsequently, multiple dosing regimens of each PERK modulator were tested in standardized, well-powered, gender-matched, and litter-matched survival efficacy studies using the SOD1G93A mouse model of ALS. The alpha-2-adrenergic receptor agonist clonidine was also tested to elucidate the results obtained from the Sephin1, and of the previously reported guanabenz studies, by comparing the effects of presence or absence of -2 agonism. The results revealed that targeting PERK may not be an ideal approach for ALS treatment. Inhibiting PERK with GSK2606414 or activating it with salubrinal did not confer therapeutic benefits. While Sephin1 showed some promising therapeutic effects, it appears that these outcomes were mediated through PERK-independent mechanisms. Clonidine also produced some favorable therapeutic effects, which were unexpected and not linked to the UPR. In conclusion, this study highlights the challenges of pharmacologically targeting PERK for therapeutic purposes in the SOD1G93A mouse model and suggests that exploring other targets within, and outside, the UPR may be more promising avenues for ALS treatment.

neuroscience↗

bioRxiv2023

Periosteal response to bone fracture at single nuclei resolution

Bone regeneration is mediated by skeletal stem/progenitor cells (SSPCs) that are mainly recruited from the periosteum after bone injury. The composition of the periosteum and the steps of SSPC activation and differentiation remain poorly understood. Here, we generated a single-nuclei atlas of the periosteum at steady-state and of the fracture site during early stages of bone repair (https://fracture-repair-atlas.cells.ucsc.edu). We identified periosteal SSPCs expressing stemness markers (Pi16 and Ly6a/SCA1) and responding to fracture by adopting an injury-induced fibrogenic cell (IIFC) fate, prior to undergoing osteogenesis or chondrogenesis. We identified distinct gene cores associated with IIFCs and their engagement into osteogenesis and chondrogenesis involving Notch, Wnt and the circadian clock signaling respectively. Finally, we show that IIFCs are the main source of paracrine signals in the fracture environment, suggesting a crucial paracrine role of this transient IIFC population during fracture healing. Overall, our study provides a complete temporal topography of the early stages of fracture healing and the dynamic response of periosteal SSPCs to injury, redefining our knowledge of bone regeneration. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/546220v3_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@d4a7bcorg.highwire.dtl.DTLVardef@1502e38org.highwire.dtl.DTLVardef@10a8e64org.highwire.dtl.DTLVardef@a6584_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Single-shot off-axis full-field optical coherence tomography

Full field optical coherence tomography (FF-OCT) enables high-resolution in-depth imaging within turbid media. In this work, we present a simple approach which combines FF-OCT with off-axis interferometry for the reconstruction of the en-face images. With low spatial and temporal coherence illumination, this new method is able to extract an FF-OCT image from only one interference acquisition. This method is described and the proof-of-concept is demonstrated through the observation of scattering samples such as organic and ex-vivo biomedical samples.

biophysics↗

bioRxiv2021

Eoulsan 2: an efficient workflow manager for reproducible bulk, long-read and single-cell transcriptomics analyses

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSCore sequencing facilities produce huge amounts of sequencing data that need to be analysed with automated workflows to ensure reproducibility and traceability. Eoulsan is a versatile open-source workflow engine meeting the needs of core facilities, by automating the analysis of a large number of samples. Its core design separates the description of the workflow from the actual commands to be run. This originality simplifies its usage as the user does not need to handle code, while ensuring reproducibility. Eoulsan was initially developed for bulk RNA-seq data, but the transcriptomics applications have recently widened with the advent of long-read sequencing and single-cell technologies, calling for the development of new workflows. ResultWe present Eoulsan 2, a major update that (i) enhances the workflow manager itself, (ii) facilitates the development of new modules, and (iii) expands its applications to long reads RNA-seq (Oxford Nanopore Technologies) and scRNA-seq (Smart-seq2 and 10x Genomics). The workflow manager has been rewritten, with support for execution on a larger choice of computational infrastructure (workstations, Hadoop clusters, and various job schedulers for cluster usage). Eoulsan now facilitates the development of new modules, by reusing wrappers developed for the Galaxy platform, with support for container images (Docker or Singularity) packaging tools to execute. Finally, Eoulsan natively integrates novel modules for bulk RNA-seq, as well as others specifically designed for processing long read RNA-seq and scRNA-seq. Eoulsan 2 is distributed with ready-to-use workflows and companion tutorials. Availability and implementationEoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL and CeCILL-C licenses at: http://outils.genomique.biologie.ens.fr/eoulsan/. The source code and sample workflows are available on GitHub: https://github.com/GenomicParisCentre/eoulsan. A GitHub repository for modules using the Galaxy tool XML syntax is further provided at: https://github.com/GenomicParisCentre/eoulsan-tools Contacteoulsan@bio.ens.psl.eu

bioinformatics↗

bioRxiv2020

Glucose-lactose mixture feeds in industry-like conditions: a gene regulatory network analysis on the hyperproducing Trichoderma reesei strain Rut-C30

BackgroundThe degradation of cellulose and hemicellulose molecules into simpler sugars such as glucose is part of the second generation biofuel production process. Hydrolysis of lignocellulosic substrates is usually performed by enzymes produced and secreted by the fungus Trichoderma reesei. Studies identifying transcription factors involved in the regulation of cellulase production have been conducted but no overview of the whole regulation network is available. A transcriptomic approach with mixtures of glucose and lactose, used as a substrate for cellulase induction, was used to help us decipher missing parts in the network. ResultsExperimental results confirmed the impact of sugar mixture on the enzymatic cocktail composition. The transcriptomic study shows a temporal regulation of the main transcription factors and a lactose concentration impact on the transcriptional profile. A gene regulatory network (GRN) built using the BRANE Cut software reveals three sub-networks related to i a positive correlation between lactose concentration and cellulase production, ii a particular dependence of the lactose onto the {beta}-glucosidase regulation and iii a negative regulation of the development process and growth. ConclusionsThis work is the first investigating a transcriptomic study regarding the effects of pure and mixed carbon sources in a fed-batch mode. Our study expose a co-orchestration of xyr1, clr2 and ace3 for cellulase and hemicellulase induction and production, a fine regulation of the {beta}-glucosidase and a decrease of growth in favor of cellulase production. These conclusions provide us with potential targets for further genetic engineering leading to better cellulase-producing strains.

bioinformatics↗

bioRxiv2017

Random Walk With Restart On Multiplex And Heterogeneous Biological Networks

Recent years have witnessed an exponential growth in the number of identified interactions between biological molecules. These interactions are usually represented as large and complex networks, calling for the development of appropriated tools to exploit the functional information they contain. Random walk with restart is the state-of-the-art guilt-by-association approach. It explores the network vicinity of gene/protein seeds to study their functions, based on the premise that nodes related to similar functions tend to lie close to each others in the networks.\n\nIn the present study, we extended the random walk with restart algorithm to multiplex and heterogeneous networks. The walk can now explore different layers of physical and functional interactions between genes and proteins, such as protein-protein interactions and co-expression associations. In addition, the walk can also jump to a network containing different sets of edges and nodes, such as phenotype similarities between diseases.\n\nWe devised a leave-one-out cross-validation strategy to evaluate the algorithms abilities to predict disease-associated genes. We demonstrate the increased performances of the multiplex-heterogeneous random walk with restart as compared to several random walks on monoplex or heterogeneous networks. Overall, our framework is able to leverage the different interaction sources to outperform current approaches.\n\nFinally, we applied the algorithm to predict genes candidate for being involved in the Wiedemann-Rautenstrauch syndrome, and to explore the network vicinity of the SHORT syndrome.\n\nThe source code and the software are freely available at: https://github.com/alberto-valdeolivas/RWR-MH.

systems biology↗